Background Cognitive symptoms after SARS-CoV-2 infection, often described as "brain fog," remain difficult to measure objectively and are biologically heterogeneous. DNA methylation may provide a stable, blood-accessible layer of information linking post-COVID immune remodeling, biological aging, and neuropsychiatric vulnerability. We re-analyzed GSE247869, a whole-blood Illumina MethylationEPIC dataset from individuals sampled six months after COVID-19 infection, to identify age-associated methylation signals with translational relevance. The present analysis was designed to characterize age-associated methylation within this post-COVID cohort, not to establish a COVID-19-specific signature or biological age acceleration. Methodology This was a cross-sectional analysis of a single post-COVID cohort, with 94 samples included in the age models and no COVID-19-negative comparator included in the analyzed model. Processed beta values were aligned to metadata, converted to M-values, and modeled at each cytosine-phosphate-guanine (CpG) using ordinary least squares with age and sex as predictors. Differentially methylated positions were corrected by Benjamini-Hochberg false discovery rate (FDR). CpGs were mapped to genes using robust annotation and Illumina manifest fallback. Gene-level signals were integrated using a multi-evidence prioritization score that incorporated statistical strength, effect size, multi-CpG support, direction consistency, known epigenetic-clock membership, and curated pathway membership. Results Within this cohort, the analysis identified 3,467 age-associated CpGs at FDR < 0.05, with an overall hypomethylation bias but focal hypermethylation at canonical aging loci. In total, 11 of 12 reference clock CpGs were recovered, including ELOVL2, FHL2, TRIM59, EDARADD, ASPA, and PDE4C. The strongest exploratory signal was enrichment of glutamatergic/N-methyl-D-aspartate (NMDA) genes, including GRIN1, GRIN2C, GRIN2D, GRM1, GRM5, and SLC17A7. GRIN1 and GRIN2C had high integrated evidence scores and showed age-associated hypermethylation. The prioritized genes mapped interpretively to glutamatergic synapse, calcium signaling, and cAMP signaling pathways, although these complete KEGG pathways were not tested as formal enrichment categories. Conclusions This re-analysis recovered established age-associated CpGs and identified age-associated methylation enrichment near glutamatergic/NMDA genes within this post-COVID cohort. It cannot determine whether these signals are specific to COVID-19 infection, reflect accelerated biological aging, or relate to cognitive symptoms because no COVID-19-negative comparator or symptom-level cognitive phenotyping was included in the present analysis. The glutamatergic finding is hypothesis-generating, particularly because the curated set was small and no independent replication cohort was analyzed. Future longitudinal and case-control studies integrating GRIN1/GRIN2C methylation with cognitive and inflammatory phenotyping are needed. Glutamatergic and calcium-signaling pathways may be evaluated in appropriately designed mechanistic and intervention studies, including but not limited to hypotheses related to the Cheung Glutamatergic Regimen, only after independent validation and careful safety evaluation.
